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2019 9th International Conference on Advances in Computing and Communication (ICACC)最新文献

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Performance Improvement of Deep Learning Architectures for Phonocardiogram Signal Classification using Fast Fourier Transform 基于快速傅立叶变换的心音信号分类深度学习体系的性能改进
2019 9th International Conference on Advances in Computing and Communication (ICACC) Pub Date : 2019-11-01 DOI: 10.1109/ICACC48162.2019.8986216
P. Gopika, V. Sowmya, E. Gopalakrishnan, K. Soman
{"title":"Performance Improvement of Deep Learning Architectures for Phonocardiogram Signal Classification using Fast Fourier Transform","authors":"P. Gopika, V. Sowmya, E. Gopalakrishnan, K. Soman","doi":"10.1109/ICACC48162.2019.8986216","DOIUrl":"https://doi.org/10.1109/ICACC48162.2019.8986216","url":null,"abstract":"Phonocardiogram known as PCG plays a significant role in the early diagnosis of cardiac abnormalities. Phonocardiogram can be used as initial diagnostics tool in remote applications due to its simplicity and cost effectiveness. Instead of disease specific approach, the proposed work aims for the single architecture that could diagnose different cardiac abnormality from the PCG signals collected from various sources. Our study also shows the effectiveness of using Fast Fourier Transform (FFT) in signal processing applications. It avoids the trivial preprocessing and feature extraction mechanisms with the promising results.","PeriodicalId":305754,"journal":{"name":"2019 9th International Conference on Advances in Computing and Communication (ICACC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116048298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
An Improved method for sharing medical images for Privacy Preserving Machine Learning using Multiparty Computation and Steganography 基于多方计算和隐写术的医学图像隐私保护机器学习共享改进方法
2019 9th International Conference on Advances in Computing and Communication (ICACC) Pub Date : 2019-11-01 DOI: 10.1109/ICACC48162.2019.8986165
R. Vignesh, R. Vishnu, S. M. Raj, M. Akshay, Divya G. Nair, Jyothisha R Nair
{"title":"An Improved method for sharing medical images for Privacy Preserving Machine Learning using Multiparty Computation and Steganography","authors":"R. Vignesh, R. Vishnu, S. M. Raj, M. Akshay, Divya G. Nair, Jyothisha R Nair","doi":"10.1109/ICACC48162.2019.8986165","DOIUrl":"https://doi.org/10.1109/ICACC48162.2019.8986165","url":null,"abstract":"Digital data privacy is one of the main concerns in today’s world. When everything is digitized, there is a threat of private data being misused. Privacy-preserving machine learning is becoming a top research area. For machines to learn, massive data is needed and when it comes to sensitive data, privacy issues arise.With this paper, we combine secure multiparty computation and steganography helping machine learning researchers to make use of a huge volume of medical images with hospitals without compromising patients’ privacy. This also has application in digital image authentication. Steganography is one way of securing digital image data by secretly embedding the data in the image without creating visually perceptible changes. Secret sharing schemes have gained popularity in the last few years and research has been done on numerous aspects.","PeriodicalId":305754,"journal":{"name":"2019 9th International Conference on Advances in Computing and Communication (ICACC)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128384245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Design of Compact Semi-circular Microstrip Antenna Loaded with Shorting Post 负载短柱的紧凑型半圆形微带天线设计
2019 9th International Conference on Advances in Computing and Communication (ICACC) Pub Date : 2019-11-01 DOI: 10.1109/ICACC48162.2019.8986169
A. Deshmukh, A. Venkata, A. Ambekar, Mohil Gala
{"title":"Design of Compact Semi-circular Microstrip Antenna Loaded with Shorting Post","authors":"A. Deshmukh, A. Venkata, A. Ambekar, Mohil Gala","doi":"10.1109/ICACC48162.2019.8986169","DOIUrl":"https://doi.org/10.1109/ICACC48162.2019.8986169","url":null,"abstract":"With an increase in the demand for personal communication systems, requirement of antennas occupying smaller area has increased which has led to the developments in compact antenna design. Many microstrip configurations using slots and shorting post have been reported. However reported work lacks in providing in-depth explanations about antenna working in terms of resonant modes and thus does not put forward any design guidelines. This paper presents a systematic study which highlight upon the behavior of antenna in terms of resonant modes of the shorted patch. Resonant length formulations for shorted patch modes and subsequent design procedure using the same have been presented, which serves as guideline in designing similar configurations at different frequencies.","PeriodicalId":305754,"journal":{"name":"2019 9th International Conference on Advances in Computing and Communication (ICACC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129253423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
ICACC 2019 Preface
2019 9th International Conference on Advances in Computing and Communication (ICACC) Pub Date : 2019-11-01 DOI: 10.1109/icacc48162.2019.8986196
{"title":"ICACC 2019 Preface","authors":"","doi":"10.1109/icacc48162.2019.8986196","DOIUrl":"https://doi.org/10.1109/icacc48162.2019.8986196","url":null,"abstract":"","PeriodicalId":305754,"journal":{"name":"2019 9th International Conference on Advances in Computing and Communication (ICACC)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126796856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A methodology for Short-term Electric Power Load Forecasting 短期电力负荷预测方法
2019 9th International Conference on Advances in Computing and Communication (ICACC) Pub Date : 2019-11-01 DOI: 10.1109/ICACC48162.2019.8986159
Smithu Izudheen, A. Joykutty
{"title":"A methodology for Short-term Electric Power Load Forecasting","authors":"Smithu Izudheen, A. Joykutty","doi":"10.1109/ICACC48162.2019.8986159","DOIUrl":"https://doi.org/10.1109/ICACC48162.2019.8986159","url":null,"abstract":"Energy consumption has been increasing steadily due to globalization and industrialization. As a result electricity load forecasting has gained vital importance in order to conserve energy and other resources. But due to the uncertain characteristics of forecasting methods, it is still one among the most difficult task to get implemented with accurate results. To predict the load, Bayesian Neural Network model based on the historical load and meteorological data of the given geographical region is presented in this article. To validate the performance of the model, meteorological and load consumption data in Kerala region over the period 2011–2012 have been used. Better accuracy and relatively shorter computing time assert that the proposed method can be used as an effective method for short-term load forecasting.","PeriodicalId":305754,"journal":{"name":"2019 9th International Conference on Advances in Computing and Communication (ICACC)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121466228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Design of an Autonomous Mobile Robot based on the Sensor Data Fusion of Lidar 360, Ultrasonic sensor and Wheel Speed Encoder 基于激光雷达360、超声波传感器和轮速编码器数据融合的自主移动机器人设计
2019 9th International Conference on Advances in Computing and Communication (ICACC) Pub Date : 2019-11-01 DOI: 10.1109/ICACC48162.2019.8986199
S. Premnath, S. Mukund, K. Sivasankaran, R. Sidaarth, S. Adarsh
{"title":"Design of an Autonomous Mobile Robot based on the Sensor Data Fusion of Lidar 360, Ultrasonic sensor and Wheel Speed Encoder","authors":"S. Premnath, S. Mukund, K. Sivasankaran, R. Sidaarth, S. Adarsh","doi":"10.1109/ICACC48162.2019.8986199","DOIUrl":"https://doi.org/10.1109/ICACC48162.2019.8986199","url":null,"abstract":"The research in improving the efficiency of the navigation of autonomous mobile robot is escalating in the field of robotics. Path planning and Obstacle avoidance are important aspects of autonomous mobile robot navigation. This requires highly accurate and robust sensors for ranging and obstacle detection. Error reduction in these sensors can be achieved using various statistical methods. The proposed technique for error reduction utilizes ANFIS system for reducing error in ultrasonic sensor and wheel speed encoder. The ANFIS models for the sensors are evaluated with different membership function for finding the one with the best RMSE. The trained ultrasonic sensor and wheel speed encoder are integrated with LiDAR, used for building an autonomous mobile robot.","PeriodicalId":305754,"journal":{"name":"2019 9th International Conference on Advances in Computing and Communication (ICACC)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132038772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 9
SAR target identification using SAR-COM technique 利用SAR- com技术识别SAR目标
2019 9th International Conference on Advances in Computing and Communication (ICACC) Pub Date : 2019-11-01 DOI: 10.1109/ICACC48162.2019.8986210
J. Anil Raj, S. M. Idicula, B. Paul
{"title":"SAR target identification using SAR-COM technique","authors":"J. Anil Raj, S. M. Idicula, B. Paul","doi":"10.1109/ICACC48162.2019.8986210","DOIUrl":"https://doi.org/10.1109/ICACC48162.2019.8986210","url":null,"abstract":"Deep learning techniques give good results on target classification of MSTAR dataset. Most of the techniques for SAR target identification use only the magnitude information of the raw SAR data and discard the phase information. Deep convolution neural network has the ability to automatically learn from the complex image generated using both the magnitude and phase information from the radar data. In this paper we are proposing a new method for generating the complex image dataset (SAR-COM) and a deep learning model which automatically classifies targets from MSTAR raw data.","PeriodicalId":305754,"journal":{"name":"2019 9th International Conference on Advances in Computing and Communication (ICACC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133577096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Alzheimer’s Disease Classification Using Deep Convolutional Neural Network 基于深度卷积神经网络的阿尔茨海默病分类
2019 9th International Conference on Advances in Computing and Communication (ICACC) Pub Date : 2019-11-01 DOI: 10.1109/ICACC48162.2019.8986170
Blessy C Simon, D. Baskar, V. Jayanthi
{"title":"Alzheimer’s Disease Classification Using Deep Convolutional Neural Network","authors":"Blessy C Simon, D. Baskar, V. Jayanthi","doi":"10.1109/ICACC48162.2019.8986170","DOIUrl":"https://doi.org/10.1109/ICACC48162.2019.8986170","url":null,"abstract":"Alzheimer’s Disease is the most common form of dementia which initially destroys the memory and finally progresses to death. This irreversible disease is mostly found among older people. The latest innovations on the multimodal neuroimaging data made it possible to detect the disease in life which was a major breakthrough in neuroscience. However, the larger degree of similarity between the brain images was the major challenge in the diagnosis. The Deep Learning technique has gained excellent results on image classification among the present researches. Hence it is utilized for the classification of brain images among Cognitively Normal (CN), Early Mild Cognitive Impairment (EMCL), Mild Cognitive Impairment (MCL), Late Mild Cognitive Impairment (LMCI), Alzheimer’s Disease (AD) which are the five classes of AD thus ensuring very precise and accurate diagnosis. The transfer learning approach has been taken up for the classification process by which three pre-trained networks, namely AlexNet, ResNet-18 and, GoogLe Net are modified and trained for 3000 images. All the three networks are trained for the same set of images which were acquired from the ADNI database.","PeriodicalId":305754,"journal":{"name":"2019 9th International Conference on Advances in Computing and Communication (ICACC)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133318123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 12
FPGA Based Low Power OFDM Transceiver For 60GHz millimeter Wave Wireless Communication Systems 基于FPGA的60GHz毫米波无线通信系统低功耗OFDM收发器
2019 9th International Conference on Advances in Computing and Communication (ICACC) Pub Date : 2019-11-01 DOI: 10.1109/ICACC48162.2019.8986175
R. S. Jini, M. N. Upama Rajan
{"title":"FPGA Based Low Power OFDM Transceiver For 60GHz millimeter Wave Wireless Communication Systems","authors":"R. S. Jini, M. N. Upama Rajan","doi":"10.1109/ICACC48162.2019.8986175","DOIUrl":"https://doi.org/10.1109/ICACC48162.2019.8986175","url":null,"abstract":"Next generation wireless communication systems such as IEEE 802.11ad millimeterWave(mmWave) WLAN and IEEE 802.15.3c mmWave WPAN devices operate in unlicenced 60GHz mmWave band. They offer multi giga bits per second (Gbps) data rate in the unlicenced band. Due to relatively high frequency of operation, the mmWave wireless networks operating in 60GHz should satisfy the power level limitations imposed by the regulatory bodies. The objective of this paper is to design and implement an FPGA based low power digital modulator for 60GHz mmWave wireless networks. In the first part of the paper we have designed an OFDM transceiver using Xilinx ISE. Later the power reduction techniques is achieved by the clock gating method. Finally a low power OFDM transceiver working in 60GHz is designed and implemented in kintex Xc7k70t-fbg676 using Xilinx ISE. The results show a significant power reduction as compared to the existing methods.","PeriodicalId":305754,"journal":{"name":"2019 9th International Conference on Advances in Computing and Communication (ICACC)","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114663823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Hybrid Reversible Image Data Hiding Scheme With Symmetric Key Cryptography 一种具有对称密钥的混合可逆图像数据隐藏方案
2019 9th International Conference on Advances in Computing and Communication (ICACC) Pub Date : 2019-11-01 DOI: 10.1109/ICACC48162.2019.8986203
G. Indramohan, K. Rama Naidu
{"title":"A Hybrid Reversible Image Data Hiding Scheme With Symmetric Key Cryptography","authors":"G. Indramohan, K. Rama Naidu","doi":"10.1109/ICACC48162.2019.8986203","DOIUrl":"https://doi.org/10.1109/ICACC48162.2019.8986203","url":null,"abstract":"This paper proposes a hybrid reversible image data hiding technique (RIDH), which is used to reconstruct an original image upon the extraction of the embedded data. Encryption and data hiding are two effective means of data protection. Encryption converts an original image into unreadable ciphertext and data hiding is used to embed additional data into image. Previous methods used secrete data hiding key for data hiding, now this paper proposes both encryption and decryption with rivest cipher 4 (RC4) and data hiding with advanced encryption standard (AES) without secrete data hiding key. Support vector machines (SVM) classifier is used to separate encrypted and non-encrypted blocks to reconstruct original image from embedded image by using feature calculation of each and every block. Evantually a trail results are given to approve the predominant execution of our method.","PeriodicalId":305754,"journal":{"name":"2019 9th International Conference on Advances in Computing and Communication (ICACC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114986601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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